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X Demographics
Mendeley readers
Attention Score in Context
| Title |
LecT-Hepa facilitates estimating treatment outcome during interferon therapy in chronic hepatitis C patients
|
|---|---|
| Published in |
Clinical Proteomics, December 2014
|
| DOI | 10.1186/1559-0275-11-44 |
| Pubmed ID | |
| Authors |
Xia Zou, Xiumei Chi, Yu Pan, Dongning Du, Haibo Sun, Atsushi Matsuda, Wei Li, Atsushi Kuno, Xinxin Zhang, Hisashi Narimatsu, Junqi Niu, Yan Zhang |
| Abstract |
A combination treatment of interferon and ribavirin is the standard and the commonly used treatment for chronic hepatitis C (CHC). Developing noninvasive tests like serum indicators that can predict treatment outcome at an early stage of therapy is beneficial for individualized treatment and management of CHC. A glyco-indicator based on the glyco-alteration of serum α1-acid glycoprotein, LecT-Hepa, was discovered by glycomics technologies as a robust indicator of liver fibrosis. Here, we investigated the clinical utility of LecT-Hepa for evaluation of treatment outcome. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 7% |
| Canada | 1 | 7% |
| Unknown | 12 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 5 | 36% |
| Researcher | 4 | 29% |
| Professor | 1 | 7% |
| Other | 1 | 7% |
| Professor > Associate Professor | 1 | 7% |
| Other | 0 | 0% |
| Unknown | 2 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 5 | 36% |
| Biochemistry, Genetics and Molecular Biology | 4 | 29% |
| Agricultural and Biological Sciences | 1 | 7% |
| Unknown | 4 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 January 2015.
All research outputs
#20,246,428
of 22,774,233 outputs
Outputs from Clinical Proteomics
#240
of 283 outputs
Outputs of similar age
#302,446
of 361,188 outputs
Outputs of similar age from Clinical Proteomics
#7
of 8 outputs
Altmetric has tracked 22,774,233 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 283 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 361,188 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 8 others from the same source and published within six weeks on either side of this one.